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Giovanni Macelloni

Researcher at International Federation of Accountants

Publications -  196
Citations -  2977

Giovanni Macelloni is an academic researcher from International Federation of Accountants. The author has contributed to research in topics: Snow & Radiometer. The author has an hindex of 25, co-authored 184 publications receiving 2439 citations. Previous affiliations of Giovanni Macelloni include National Research Council.

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The relationship between the backscattering coefficient and the biomass of narrow and broad leaf crops

TL;DR: Multifrequency multitemporal polarimetric data showed that the relations between the backscattering of crops and the vegetation biomass depend on plant type, and that there are different trends for "narrow" and "broad" leaf crops.
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Cold Regions Hydrology High-Resolution Observatory for Snow and Cold Land Processes

TL;DR: The scientific drivers and technical approach of the proposed Cold Regions Hydrology High-Resolution Observatory (CoReH2O) satellite mission for snow and cold land processes are described and the dual-frequency and dual-polarization design enables the decomposition of the scattering signal for retrieving snow mass and other physical properties of snow and ice.
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A multifrequency algorithm for the retrieval of soil moisture on a large scale using microwave data from SMMR and SSM/I satellites

TL;DR: An algorithm is proposed for the retrieval of soil moisture based on the sensitivity to moisture of both the brightness temperature and the polarized index at C-band, one that is able to correct for the effect of vegetation by means of the polarization index at X-band.
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Changing Arctic Snow Cover: A Review of Recent Developments and Assessment of Future Needs for Observations, Modelling, and Impacts

TL;DR: Advances in snow monitoring and modelling are reviewed, and the impact of snow changes on ecosystems and society in Arctic regions is reviewed, to improve the ability to predict manage and adapt to natural hazards in the Arctic region.
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Soil Moisture Estimates From AMSR-E Brightness Temperatures by Using a Dual-Frequency Algorithm

TL;DR: The soil moisture estimated by the algorithm from AMSR-E data and the SMC measured on the ground were in good agreement with each other in both sites, and five classes of soil moisture were easily identified.